Abstract
Data collected from mobile phones have potential knowledge to provide with important behavior patterns of individuals. In this paper, we present approaches to discovering personal mobility and characteristics based on mobile phone location information and semantic analysis. We discuss three aspects related to very common mobile phone-related applications such as pattern mining, semantic label identification and movement prediction. We use real mobile phone data to perform functions of discovering these behavior patterns and demonstrate effectiveness of our approaches.
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Xie, R., Luo, J., Yue, Y., Li, Q., Zou, X. (2012). Pattern Mining, Semantic Label Identification and Movement Prediction Using Mobile Phone Data. In: Zhou, S., Zhang, S., Karypis, G. (eds) Advanced Data Mining and Applications. ADMA 2012. Lecture Notes in Computer Science(), vol 7713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35527-1_35
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DOI: https://doi.org/10.1007/978-3-642-35527-1_35
Publisher Name: Springer, Berlin, Heidelberg
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